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Understanding viral video dynamics through an epidemic modelling approach

Author

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  • Sachak-Patwa, Rahil
  • Fadai, Nabil T.
  • Van Gorder, Robert A.

Abstract

Motivated by the hypothesis that the spread of viral videos is analogous to the spread of a disease epidemic, we formulate a novel susceptible–exposed–infected–recovered–susceptible (SEIRS) delay differential equation epidemic model to describe the popularity evolution of viral videos. Our models incorporate time-delay, in order to accurately describe the virtual contact process between individuals and the temporary immunity of individuals to videos after they have grown tired of watching them. We validate our models by fitting model parameters to viewing data from YouTube music videos, in order to demonstrate that the model solutions accurately reproduce real behaviour seen in this data. We use an SEIR model to describe the initial growth and decline of daily views, and an SEIRS model to describe the long term behaviour of the popularity of music videos. We also analyse the decay rates in the daily views of videos, determining whether they follow a power law or exponential distribution. Although we focus on viral videos, the modelling approach may be used to understand dynamics emergent from other areas of science which aim to describe consumer behaviour.

Suggested Citation

  • Sachak-Patwa, Rahil & Fadai, Nabil T. & Van Gorder, Robert A., 2018. "Understanding viral video dynamics through an epidemic modelling approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 416-435.
  • Handle: RePEc:eee:phsmap:v:502:y:2018:i:c:p:416-435
    DOI: 10.1016/j.physa.2018.02.083
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    Cited by:

    1. Sachak-Patwa, Rahil & Fadai, Nabil T. & Van Gorder, Robert A., 2019. "Modeling multi-group dynamics of related viral videos with delay differential equations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 197-217.
    2. Sang, Chun-Yan & Liao, Shi-Gen, 2020. "Modeling and simulation of information dissemination model considering user’s awareness behavior in mobile social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    3. Jung, Hohyun & Phoa, Frederick Kin Hing, 2021. "On the effects of capability and popularity on network dynamics with applications to YouTube and Twitch networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).

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